Pre and During COVID-19 Access to Rural Mental Health Care Among Agriculture Communities in the Rocky Mountain Region.

Death by suicide is the second leading cause of intentional injury incurred by foreign-born workers in the United States. Hispanic/Latino farmworkers are systematically excluded from important safety net programs. Drawing on interviews with 16 individuals representing various community organizations serving rural, agriculture-dependent regions in Colorado (n=9) and Utah (n=7), we describe Hispanic/Latino farmworkers' access to the mental health safety net in the Rocky Mountain Region post/during the COVID-19 pandemic. Findings inform the need for expanded safety net infrastructure and community collaborations to support farmworkers effectively now and in the case of future pandemics.

County-level analysis on occupation and ecological determinants of child abuse and neglect rates employing elastic net regression.

BACKGROUND: Occupation is a known determinant of worker physical and behavioral health risk, yet most previous studies have focused on unemployment, underemployment, and job satisfaction to understand child maltreatment risk. OBJECTIVE: This county-level study (n = 278) investigated the association between occupation and child maltreatment rates and community well-being in California, Colorado, Minnesota, Oregon, and New Mexico. PARTICIPANTS AND SETTING: States were selected due to having comparable, publicly available county-level data on substantiated child abuse and neglect rates within a five-year span between 2015 and 2020. METHODS: Using US Census Bureau American Community Survey data, we collected percentages of the employed population among 13 occupations. Five additional community health indicators came from the County Health Rankings and Roadmaps. Elastic net linear regression was used for variable selection and because of explanatory variables' interrelationships. Linear regression was used to model individual industries positively associated with child abuse rates. RESULTS: The elastic net model selected ten important variables in explaining child maltreatment rates. Important occupational sectors were agriculture, forestry, fishing (AFF), manufacturing, wholesale, retail, finance, and education. Important community indicators included housing, injury deaths, and poor mental health days. Only AFF and retail showed greater child abuse rates with increasing percentages of the workforce in these occupations in unadjusted models (AFF: ß = 0.03 SE = 0.01, p = 0.02; Retail: ß = 0.09 SE = 0.04, p = 0.02). CONCLUSIONS: Our findings suggest group-level effects of counties with a larger AFF and retail presence experiencing higher child maltreatment rates. Given that numerous prior studies of county economies note the strong associations of certain employment types with cultural attitudes, educational opportunities, regional biases, and other unmeasured variables, future studies should incorporate individual level data in a multilevel framework.